mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-24 18:24:20 +00:00
fix
This commit is contained in:
parent
d8ed7cd179
commit
a0cb56efd5
1 changed files with 11 additions and 25 deletions
|
@ -15,15 +15,11 @@ class AnthropicError(Exception):
|
|||
def __init__(self, status_code, message):
|
||||
self.status_code = status_code
|
||||
self.message = message
|
||||
super().__init__(
|
||||
self.message
|
||||
) # Call the base class constructor with the parameters it needs
|
||||
super().__init__(self.message) # Call the base class constructor with the parameters it needs
|
||||
|
||||
|
||||
class AnthropicLLM:
|
||||
def __init__(
|
||||
self, encoding, default_max_tokens_to_sample, logging_obj, api_key=None
|
||||
):
|
||||
def __init__(self, encoding, default_max_tokens_to_sample, logging_obj, api_key=None):
|
||||
self.encoding = encoding
|
||||
self.default_max_tokens_to_sample = default_max_tokens_to_sample
|
||||
self.completion_url = "https://api.anthropic.com/v1/complete"
|
||||
|
@ -31,9 +27,7 @@ class AnthropicLLM:
|
|||
self.logging_obj = logging_obj
|
||||
self.validate_environment(api_key=api_key)
|
||||
|
||||
def validate_environment(
|
||||
self, api_key
|
||||
): # set up the environment required to run the model
|
||||
def validate_environment(self, api_key): # set up the environment required to run the model
|
||||
# set the api key
|
||||
if self.api_key == None:
|
||||
raise ValueError(
|
||||
|
@ -62,19 +56,13 @@ class AnthropicLLM:
|
|||
for message in messages:
|
||||
if "role" in message:
|
||||
if message["role"] == "user":
|
||||
prompt += (
|
||||
f"{AnthropicConstants.HUMAN_PROMPT.value}{message['content']}"
|
||||
)
|
||||
prompt += f"{AnthropicConstants.HUMAN_PROMPT.value}{message['content']}"
|
||||
else:
|
||||
prompt += (
|
||||
f"{AnthropicConstants.AI_PROMPT.value}{message['content']}"
|
||||
)
|
||||
prompt += f"{AnthropicConstants.AI_PROMPT.value}{message['content']}"
|
||||
else:
|
||||
prompt += f"{AnthropicConstants.HUMAN_PROMPT.value}{message['content']}"
|
||||
prompt += f"{AnthropicConstants.AI_PROMPT.value}"
|
||||
if "max_tokens" in optional_params and optional_params["max_tokens"] != float(
|
||||
"inf"
|
||||
):
|
||||
if "max_tokens" in optional_params and optional_params["max_tokens"] != float("inf"):
|
||||
max_tokens = optional_params["max_tokens"]
|
||||
else:
|
||||
max_tokens = self.default_max_tokens_to_sample
|
||||
|
@ -93,9 +81,11 @@ class AnthropicLLM:
|
|||
)
|
||||
## COMPLETION CALL
|
||||
response = requests.post(
|
||||
self.completion_url, headers=self.headers, data=json.dumps(data)
|
||||
self.completion_url, headers=self.headers, data=json.dumps(data), stream=optional_params["stream"]
|
||||
)
|
||||
print(optional_params)
|
||||
if "stream" in optional_params and optional_params["stream"] == True:
|
||||
print("IS STREAMING")
|
||||
return response.iter_lines()
|
||||
else:
|
||||
## LOGGING
|
||||
|
@ -114,14 +104,10 @@ class AnthropicLLM:
|
|||
status_code=response.status_code,
|
||||
)
|
||||
else:
|
||||
model_response["choices"][0]["message"][
|
||||
"content"
|
||||
] = completion_response["completion"]
|
||||
model_response["choices"][0]["message"]["content"] = completion_response["completion"]
|
||||
|
||||
## CALCULATING USAGE
|
||||
prompt_tokens = len(
|
||||
self.encoding.encode(prompt)
|
||||
) ##[TODO] use the anthropic tokenizer here
|
||||
prompt_tokens = len(self.encoding.encode(prompt)) ##[TODO] use the anthropic tokenizer here
|
||||
completion_tokens = len(
|
||||
self.encoding.encode(model_response["choices"][0]["message"]["content"])
|
||||
) ##[TODO] use the anthropic tokenizer here
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue